In New York Times I saw the article “I.B.M. Researchers Inch Toward Quantum Computer.” It was quite surprising, the quest to build a quantum computer. I thought it would be good to analysis the problem, present a view of the sate-of-art and to share it with those who are some how engaged in this domain or any related felid.

First I flashed back the thunderous days that IBM produced PCs. Then I thought how science especially physics is engaging more and more to computer science and engineering problems. I think that the name of Quantum is still somehow an idealistic concept to engineers so you can imagine how it feels to reach Quantum Computer.

The interesting matter is, this field is the province of academia, usually you can hear about this project in universities or research laboratories. Many university researchers have advanced and developed the basic scientific problems. Scientists have encouraged the company to pay attention to this project, though it’s too early to have a plan for a commercial product. Dr. Ketchen said: “It’s going to take an IBM in the end to put it together.

For me what makes sense is that IBM takes step forward into this domain. After all I think that it’s very good news to us and I guess that the future is beginning to be created or even has begun.

The biggest challenges would be how lengthening the quantum bits or shortly qubits lifetime and quickening the pace of computation. IBM researches will present their experimental results that they say that close them to solve the problem on Tuesday in Boston.

Let’s take a look at to our actual problems and challenges in computer engineering. Today the world of informatics is based on binary calculations, we describe the signal as 1s and 0s in signal transfer, using coding technics like Manchester coding in digital signals and we transfer signals in the analog form for log distance distribution using sinusoid waves.

Currently we’re bounded by hardware and electrical constraints like resistance of conductors, capacity of carriers, limitation of Signal to Noise (Shannon’s Law) and transfer of signals.

Most of the computer science experts challenge with systems and operating systems to reduce the process time. In the point of view of the system, we deal with system architecture and design, reducing dimension of circuits while having the best performance and reducing energy consumption of the system witch has an irresistible effect on system performance. In the point of view of operating systems, challenges are choosing best algorithm for managing process timing and Input/Output devices, preventing and managing the dead ends, parallelizing processes and the problem of having a well-fitted operating system for multi processor and distributed systems.

Regarding to the state-of-art, for many processes even super computers may get occupied for hours or days. Quantum computers solve problems that would occupy present-day computers for years.

"In quantum mechanics, multiple possibilities exist at once and a qubit is not necessarily a 1 or 0, but a combination of both. By stringing together qubits, a quantum computer could perform a multitude of calculations simultaneously. For certain problems like searching databases and or factoring large numbers the basis of today’s encryption technics, quantum computer could produce an answer in days or maybe even seconds, whereas the fastest conventional computer would take longer than 13.7 billion years.

The I.B.M. researchers are building quantum computer components out of electronic circuits containing superconductors, materials that carry electricity without electrical resistance. When cooled to a hundredth of a degree above absolute zero, the circuits act as qubits.

The problem is that a qubit becomes scrambled in short order, and the information it carries turns into gibberish. When physicists started experiments a little more than a decade ago, a qubit lasted only a few billionths of a second. (An alternate approach, trapping ions in electric and magnetic fields, can produce longer-lived qubits. But the superconducting circuit approach takes advantage of current computer chip technologies.)In the latest I.B.M. results, which build on a technique developed by Robert J. Schoelkopf, a physics professor at Yale, a qubit lasted as long as one-10,000th of a second.Even though that is still not long enough for perfect calculations, it is almost good enough for error correction algorithms to detect and fix any mistakes. “We’re just crossing this threshold,” Dr. Ketchen said, “which is a big morale booster that says, gee, this is becoming doable.

Below the threshold, generating reliable answers is impossible. “No matter how many qubits you had, you couldn’t even get one effectively good one because of the error rates being too high,” he said." "

We may think of the programming methods, compatibility of compilers and linkers, machine language and thousands of questions that may make our mind busy, but instead of these questions and thinking of the dark sides, I believe that it’s better to have hope, continuing researches and having hope, because the future is bright.

From a patient’s perspective, one would hope that medicine was always based on the rational use of evidence and not simply dispensed arbitrarily at the practitioner’s whim. However, with the rapidly increasing volume of medical research being conducted and clinical laboratory tests being developed, doctors are challenged increasingly on how best to integrate evidence in making decisions about the day-to-day care of their patients.

Regarding advances in technology and medicine, there exist different resources of studying evidences for doctors to precept therefore effective usage of evidences in making decision is getting increasingly important. There are many ways to dissect the complicated process of decision making. We face certain challenges likely which decision would be optimal. How to make decision in a minimal period of time. How to decrease the the tolerance of fault decision, regarding its social and mental effects. Many biases can occur at every phase of doctors interactions with patients and the aim is to find a solution to minimize them. No surefire methods exist for eliminating biases in medical decision making, but there is some evidence that the adoption of an evidence-based medicine approach or the incorporation of formal decision analytic tools can improve the quality of doctors reasoning. By taking these and other possible issues into account, it is recommended to consider diagnosis and treatment as rational procedure. In a common approach, the procedure is a sequential steps of making a diagnosis and choosing a course of treatment. By this approach, we have a sequential demonstration of all information which are classified and connected by rational procedure. This will make it easier to choose optimal evidences, this helps to obtain a result with less complexity. By having a transparent demonstration of further phases of diagnosis, the rationality of the approach conduct us to a decision with less uncertainty. The positive point here is that by having a rational vision of the procedure we can evaluate the functionality. In order to obtain an optimal diagnosis having a clear vision on functionality which is the result of rationality would not be enough. And we can pose the question, is the diagnosis useful? In the other word, by having only rational vision we cannot judge the usefulness of the approach. Functionality is not all there is to the pragmatic choice situation. The ultimate choice has to be a balancing between functionality and usefulness. Therefore, not all the rational choices will be in accord with the recommendations that we have discussed so far. These considerations about usefulness may seem to undermine the whole idea that functionality and positive evidence are so important. But functionality is important to usefulness simply because nothing is useful unless it works.A decision is a choice made by some entity of an action from some set of alternative actions. A good decision identifies an alternative that the decision maker believes will prove at least as good as other alternative actions. Good decisions are formally characterized as actions that maximize expected utility, a notion involving belief, goodness and usefulness.

Therefore the decision theory is important because by choosing the the best action between variety of rational alternatives we can have a clear vision of different possible diagnosis, evaluate different rational choices and useful set of actions, and discuss these possibilities with patient. The advantage is that having this approach we can involve patient in the decision making process. This procedure will lead to optimal diagnosis.

The traditional approach of the organizations to increase their computation and data capacity was to buy more hardware and improve their IT operations.

From the costumer point of view IT is considered as a “Utility” it can be bought more or less.

Cloud computing, as defined by the US National Institute of Standards and Technology, offers a drastically different approach to IT resource delivery, allowing users to lease data and processing capacity from a "cloud" of interconnected computing systems, maintained by someone else and shared by others, to the level required.

From about 2008 that Microsoft started introducing cloud computing by presenting some services embedded in email service and from about 2009 Apple by its MobileMe by offering different services, until today we may can say that many horizons are being operational.

There exists several cloud computing providers offering different kinds of services like storage, with different levels of access policies for sharing files. The famous ones are Microsoft, IBM and Apple.

From the wide range services of Microsoft Azure and iCloud in the domain of market, to the new methodologies in business modeling policies and related software engineering approaches, we observe that in universities, laboratories and organizations we are developing this new domain.

The potential benefits of this approach to service delivery include a focus on core business (software service delivery versus platforms), a rental model (versus purchase and maintain), and platform provider-maintained capabilities that might otherwise be challenging (for example, pay-per-use of service, service integration, security systems, and hardware and OS maintenance).

Many Issues

On my opinion, the most important concept that helped cloud computing to grow may be Software Engineering. Cloud computing benefits software engineering concepts like agility, availability and cost efficiency. These need to well engineered for cloud platforms.

Regarding to the recent developments in this domain many open issues surround the use of software services from the cloud:

Independently, each of these aspects must be addressed in the phase of engineering practical cloud-based services and solutions.

Requirement

Requirement engineering for cloud services is a reach research area that hasn’t received much attention. Besides the traditional methods, there are unique challenges in cloud projects that in the future I will discuss on them.

In this part I present a short introduction. For example, in requirement acquisition phase, organizations must gain a better understanding of their real needs for cloud, this will cause in gathering requirements, both side (organization and the engineering team) change their representation method of the goals, needs and perspective. This means that besides traditional top-level business goals such as reducing cost and complexity they think of categorizing their needs to be represented as a special service by cloud such as PaaS, IaaS and etc. I should refer here to my post published in my weblog in February 2012. It should be noted that this horizon is applicable within a good collaboration during meetings of the organization and the engineering team.

Having different views on the cloud computing, as I have read in different magazines, journals, papers and seen in communities and conferences we have almost reached an agreement on the basic styles on it. These styles can be categorized as follow:

I. SAAS (Software as a service)

This kind of cloud computing transfer programs to millions of users through browser. In the user’s views, this can save some cost on servers and software. In the provider’s views, they only need to maintain one program, this can also save cost. SAAS is commonly used in human resource management system and ERP (Enterprise Resource Planning).

II. Utility Computing

Recently Amazon.com, Sun, IBM and other companies that provide storage services and virtual services are appearing. Cloud computing is creating virtual data center for IT industry to make it can provide service for the whole net through collecting memory, IO equipment, storage and computing power to a virtual resource pool.

III. Network service

Network services have a close relation with SAAS. These services providers can help programmers develop applications based on internet instead of providing single machine procedure through providing API (Application Programming Interface).

IV. PAAS ( Platform as a service)

Platform as a service, another SAAS, this kind of cloud computing providing development environment as a service. We can use the middleman’s equipment to develop our own program and transfer it to the users through internet and servers.

V. MSP (Management service provider)

This is one of the ancient applications of cloud computing. This application mostly serves the IT industry instead of end users. It is often used in mail virus scanning and program monitoring.

VI. Integrating internet

It can integrate all the companies that provide similar services, so that users can compare and select their service provider.

VII. Commercial service platform

The commercial service platform is the mixture of SAAS and MSP (Mixed signal Processor), this kind of computing provides a platform for the interaction between users and service provider. For instance, the user individual expense management system can manage user’s expense according user’s setting and coordinate all the services that users purchased.